- Research article
- Open Access
Excitatory repetitive transcranial magnetic stimulation to left dorsal premotor cortex enhances motor consolidation of new skills
© Boyd and Linsdell; licensee BioMed Central Ltd. 2009
- Received: 25 February 2009
- Accepted: 07 July 2009
- Published: 07 July 2009
Following practice of skilled movements, changes continue to take place in the brain that both strengthen and modify memory for motor learning. These changes represent motor memory consolidation a process whereby new memories are transformed from a fragile to a more permanent, robust and stable state. In the present study, the neural correlates of motor memory consolidation were probed using repetitive transcranial magnetic stimulation (rTMS) to the dorsal premotor cortex (PMd). Participants engaged in four days of continuous tracking practice that immediately followed either excitatory 5 HZ, inhibitory 1 HZ or control, sham rTMS. A delayed retention test assessed motor learning of repeated and random sequences of continuous movement; no rTMS was applied at retention.
We discovered that 5 HZ excitatory rTMS to PMd stimulated motor memory consolidation as evidenced by off-line learning, whereas only memory stabilization was noted following 1 Hz inhibitory or sham stimulation.
Our data support the hypothesis that PMd is important for continuous motor learning, specifically via off-line consolidation of learned motor behaviors.
- Transcranial Magnetic Stimulation
- Tracking Error
- Motor Learning
- Retention Test
- Sham Stimulation
It is clear that skilled practice is essential for the acquisition of learned motor behaviors [1–3] and that the brain continues to process information from practice sessions well beyond the timeframe of motor performance [4–7]. In fact, many changes take place after practice that both strengthen and modify the motor skill being learned. These changes represent motor memory consolidation [5–7] a process whereby new, fragile memories are transformed into more permanent, robust and stable state.
Consolidation of motor skill memories has been purported to take two forms: 1) off-line improvements in behavior that occur in between practice sessions, and 2) memory stabilization which reduces the fragility or susceptibility to interference by other motor actions while behavioral improvements are maintained [6–9]. While these two elements of motor consolidation are not completely independent of one another, the degree to which they interact and/or rely of unique neural structures remains unclear.
Functional brain imaging has been used to consider how the neural structures associated with movement change as motor learning occurs [5, 10, 11]. Following practice, while motor ability remains unchanged, positron emission tomography shows that the brain recruits new regions to perform the task. Early in motor skill acquisition prefrontal brain regions are active. Later, there is a shift in activation to premotor, posterior parietal and cerebellar structures . Evolution of the network activated in association with motor learning is widely believed to support motor consolidation or the increase in stability of the new skill [5–7, 11].
Intracortical recordings in animals and human neuroimaging studies indicate that the premotor cortex (PMC) plays an important role in the selection of movements [12, 13]. The PMC can be functionally segregated according to the type of movement being selected [14–18]. The ventral premotor (PMv) cortex is involved in grasping movements that are externally triggered by the environment , while the dorsal premotor (PMd) cortex appears to be particularly important in the selection movements that are learned [12, 19].
At present it is unclear whether PMd is important for selecting learned movements  or for learning new movements [21, 22]. Some animal work suggests that PMd is involved in motor learning. The PMd cortex may be critical for holding sensory information in working memory and then converting it to a motor program . Single cell recordings from PMd during motor task practice demonstrate the emergence of new motor programs that are based on the sensory information acquired through practice . Other research in humans, suggests a dominance of left PMd for the selection of learned movements [12, 19]. Functional magnetic resonance imaging (MRI) studies show that only right PMd is active during movements of the left hand; however, left PMd is activated during movements of both the right and left hands . The disparate nature of PMd activity during movements of each hand has also been confirmed by transcranial magnetic stimulation (TMS) studies demonstrating that disruption of left PMd alters movements in both hands .
Though past work has purported to investigate the role of PMd in skill acquisition it has often been limited by the failure to consider motor learning at a separate delayed retention test [7, 23] but rather has largely considered behavioral changes across a single day or session. Without data from separate sessions it is impossible to evaluate the impact of any intervention of the long-term, permanent ability to perform new motor skills . Because we were interested in the possibility that PMd might play a role in consolidation of new motor learning we designed the present experiment to contain practice sessions and a delayed retention test, which were all conducted on separate days.
To investigate the role of PMd in motor skill learning we coupled brain stimulation with motor-skill acquisition, pairing the delivery of an epoch of excitatory (5 Hz) repetitive TMS (rTMS) with movement task practice. To verify the effects of excitatory rTMS, we also trained a group of individuals who only received inhibitory (1 Hz) rTMS and another cohort who received sham stimulation. Because of the known role of PMd in motor learning and its purported role in the stabilization of newly acquired skills, we hypothesized that excitatory rTMS to PMd would facilitate motor skill consolidation.
Subject characteristics for the Excitatory, Inhibitory, and Sham groups
Age (years ± sd)
24 ± 2
24 ± 1
27 ± 7
6 M, 4 F
3 M, 7 F
5 M, 5 F
The middle (repeated) segment was constructed by using the same coefficients for every trial (Appendix 1). The first and third segments of the tracking pattern were generated randomly using coefficients ranging from 5.0 to -5.0. A different random sequence was used for both the first and third segments for every trial (Figure 1B); however, to ensure uniformity across participants the same set of trials were practiced by all of the participants so that on any given trial the random segments were the same for each participant. In each third of the tracking pattern there were 10 separate reversals in the direction. The trajectories of the target and participants' movements did not leave a trail and thus, participants could not visualize the entire target pattern.
The same trial order was employed for every participant. Participants were not informed of the existence of the repeating sequence but instructed daily to track the target as accurately as possible by controlling the position of the cursor with the joystick.
Application of TMS was performed with a 70 mm figure-8 air-cooled coil (Magstim Super Rapid2, Magstim Company, Ltd.). The magnetic stimulus had a biphasic waveform with a pulse width of 400 u s. During stimulation of both M1 for thresholding and PMd for repetitive stimulation the TMS coil was oriented tangentially to the scalp with the handle pointing back and away from midline at 45 degrees. Prior to the start of the experiment each participant underwent an anatomical MRI scan on a separate day at the UBC 3T MRI Centre (T1 images TE = 5 ms, TR = 24 ms, 40° flip angle, NEX = 1, thickness = 1.2 mm, FOV = 256 mm). These images were imported into Brainsight™ TMS neuronavigation software (Rogue Research Inc.) to allow for stereotaxic registration of the participant's brain with TMS coil for online control of coil positioning.
Several steps were taken to ensure that stimulation of PMd without M1 during rTMS. First we used a coil that has previously been shown to have a focal enough output to stimulate PMd in isolation. Application of TMS was performed with a 70 mm figure-8 air-cooled coil (Magstim Super Rapid2, Magstim Company, Ltd.). Past work has demonstrated that a 70 mm coil can deliver focal stimulation  with a current spread small enough, 10 × 10 × 20 mm , to stimulate M1 without PMd and vice versa. Second, we oriented our coil over the PMd using anatomic landmarks shown via each individual's T1 MRI to guide us to the posterior aspect of the middle frontal gyrus.[21, 35] Once confirmed, the location of PMd and the direction of our stimulation were maintained both within and across sessions by trajectory targeting using BrainSight.
Mean (standard deviation) RMT from day 1 and day 5 of the experiment by group.
Mean (standard deviation) adjusted %RMT for rTMS from days 1 to 4 of the experiment for the Excite and Inhibit groups.
Because a 15 minute bout of rTMS has been shown to induce approximately a 15-minute after-effect, individuals underwent rTMS first, then immediately practiced the motor task on each of the four practice days. This structure was identical regardless of the rTMS group assignment.
Design and procedures
The experiment lasted for five days spread over a 2-week timeframe. Days 1–4 were training (rTMS paired with motor task practice). In each of these days participants performed 3 blocks (30 trials) of tracking. Tracking was performed immediately after application of rTMS. Participants were given 2 weeks to complete the entire 5-day experiment, but no more than one day lapsed between day 4 of practice and the retention test for any subject. That is, retention testing always occurred within 48 hours of the last practice session. However, it was necessary to allow days between practice sessions in order to accommodate individual participants' schedules.
To better separate performance effects from more permanent changes in behaviour associated with learning , a retention test consisting of 1 block of continuous tracking was given on a separate 5th day. No rTMS was administered at the retention test.
Repeated sequence awareness
On day 5 following the retention test block, participants were shown 10, 30s blocks (all 3 sequences) of continuous target movement and asked to decide if they recognized any as the pattern that they had seen during practice. Three of the 10 were "true" middle sequence i.e., the same as the repeated practice pattern; 7 were foils. Individuals who identified the repeated sequence at a better than chance rate, i.e., 2 of 3 repeated sequences identified correctly as being recognized and 4 of 7 novel, random epochs identified correctly as never having been seen before, were considered to have gained explicit awareness of the repeating sequence.
Motor performance was evaluated across practice and retention. Our analysis considered changes in root mean squared error (RMSE; Appendix 2), which reflects overall tracking error in the kinematic pattern and is the average difference between the target pattern and participant movements. This score was calculated separately for random and repeating sequences on every tracking trial and averaged by block (every 10 trials)[27, 28, 43]. Comparison between RMSE from the repeated and random sequences reflects sequence specific learning. This measure was used to evaluate reductions in tracking errors across practice and at retention.
To investigate the possibility that rTMS stimulated off-line motor learning we calculated a change score to reflect the difference in tracking error at the end of practice with that at the retention test. This computation was performed for both repeated and random sequences. We assume that continued further decrease in tracking error (RMSE) between the last practice block and the retention test reflects off-line motor learning associated with consolidation [6, 7].
Prior to running analyses of variance on our motor practice and learning data the normality of distribution was assessed with a Kolmogorov-Smirnov test. The data were normally distributed. Overall, our analyses were conducted in three steps. First, we considered performance related changes across the four experimental days when practice was paired with rTMS. Second, we assessed motor learning at the retention test on day 5. Third, we assessed offline learning. We defined off-line learning related gains according to Robertson (2004, 2006) as the difference in RMSE in between the last block of practice on day 4 (when rTMS was last delivered) and the retention test on day 5 when there was no rTMS. Our retention test was delivered within 48 hours of the last practice day to ensure that we assessed off-line learning within the accepted time frame.[7, 44]
Acquisition practice. Performance of the repeated sequence during practice was examined using two factor (Group [Excite, Inhibit, Sham] X Block [1-12]) repeated measures ANOVA. This analysis was performed separately with repeated sequence RMSE and random sequence RMSE as the dependent variables.
Retention. Motor learning at retention was examined via a Group [Excite, Inhibit, Sham] by Sequence [Random, Repeated] repeated measures ANOVA with RMSE or tracking error as the dependent measure. A Bonferroni correction was used for post-hoc tests to determine the locus of significant group by sequence interactions. Off-line motor learning was assessed via a one-way ANOVA using the change score from the last block of practice to the retention test as the dependent measure. This test was performed separately for random and repeated sequence change scores.
Overall, our data demonstrate three main results. First, regardless of stimulation condition tracking error as reflected by RMSE decreased with practice. Second, at the retention test all groups showed motor learning of the repeated sequence; however, the largest amount of change between repeated and random sequence tracking error was shown by the Excite group. Third, consideration of gains made in tracking accuracy between the last block of practice and the retention test demonstrate off-line motor learning for the Excite group but not for the Inhibit or Sham groups.
None of the experimental groups gained explicit knowledge of the repeating sequence as demonstrated by the ability to identify the repeating sequence during recognition tests on the final day at chance.
Even single sessions of motor practice can lead to long-term storage of movement representations in the brain . It is now clear that after practice has ended the functional properties and representation of skilled movement continues to evolve in the brain [4–7]. These changes are evident in the gradual development of resistance to interference from other behaviours as time passes after task practice [4, 5]. In some cases motor skills are not merely stabilized but can be improved through this consolidation process [6, 7]. Indeed, this is what we discovered when we paired 5 Hz excitatory rTMS to left PMd with motor task practice; motor skill continued to improve off-line after practice. Conversely, participants who practiced the motor task and received either inhibitory or sham stimulation showed only memory stabilization, there was no further between session improvement, but rather a relative preservation in motor skill level acquired via practice . Though these two forms of memory consolidation are not mutually exclusive, our data suggest that PMd has a role in off-line motor skill enhancement. Importantly, we separated the short-term effects of practice from more permanent changes in behaviour demonstrated at retention by performing these tests on different days . This experimental feature allowed us to view off-line learning in the Excite group without any interference effects from practice .
Critically, the off-line motor consolidation demonstrated by the Excite group was related to sequence-specific motor learning rather than to generalized improvements in motor control associated with task practice. Illustration of this point is evident in the difference in tracking error across groups for the repeated sequence at retention (Figure 4); the three groups demonstrated equivalent performance on random sequences at the same time. Random sequence tracking reflects generalized motor execution whereas repeated sequence performance shows motor learning [27, 28, 43]. Thus, the role of PMd in motor consolidation in the present work related to implicit sequence-specific learning rather than an overall improvement in the generalized ability to track continuous sequences.
There has been debate as to whether PMd activity relates to motor learning  or to the recall of already learned movements [5, 20]. Our data support the hypothesis that PMd activity facilitates motor learning, specifically by aiding memory consolidation. Two features of our data support our conclusion. Critically, excitatory stimulation to PMd promoted off-line learning. We expected that if PMd played a role in recall of learned movements rather than in motor learning, we would have noted memory stabilization rather than off-line improvements. Second, the improvements associated with excitatory stimulation to PMd were sequence-specific and not simply related to generalized motor control improvements.
The influence of PMd activity on motor learning and memory consolidation likely operated though a network of brain regions. PMd is ideally situated to impact a broad range of cortico-cortical and cortic-subcortical networks. On-line rTMS-fMRI imaging has shown that excitatory stimulation of PMd increases the BOLD signal both locally (in PMd, PMv, supplementary motor area, somatosensory cortex, and cingulate motor area) and distantly (in contralateral PMd, cerebellum, putamen and caudate; ). Further, these rTMS driven modifications in hemodynamics occur even in the absence of overt motor responses. This pattern of brain activation associated with rTMS to PMd reflects the known anatomical and functional connectivity amongst these regions [14, 15, 45]. Though we cannot ascribe the offline learning we documented to any single region within this broad network, it is evident that 5 Hz rTMS stimulated motor memory consolidation most likely via up-regulating at least some elements of both local and distantly connected brain regions.
We expected that the Inhibit group might have demonstrated worse behaviour than those participants in the Sham stimulation condition. However, it may be that the positive effects of practice on accuracy of motor tracking performance countered the impact of 1 Hz stimulation. Indeed, we and others [26–28, 46] have shown that motor task practice of continuous tracking tasks may be well learned over as few as three practice sessions. It is possible that in the present study the effects of 1 Hz TMS was either overcome by motor practice or that the network of brain regions associated with motor learning [5, 21, 45] was able to compensate for less PMd function following inhibitory stimulation.
Though sleep may have played a role in the consolidation we noted across our experimental groups it cannot explain the lower tracking error for repeated sequences shown only by the Excite group at retention. Each of our groups slept in between the last practice day and the retention test; conferring the benefit of sleep on motor skill consolidation regardless of group assignment. Further, past work has demonstrated that off-line improvements in implicit motor learning in young, healthy controls are not sleep dependent . Instead, sleep related improvements in motor skill may develop equally well over the day as they do over the night . Thus, we do not believe that the sleep-induced benefits that are associated with consolidation can account for our findings.
It is also unlikely that differences in explicit knowledge explain any of our group differences across practice or at retention; none of the groups gained explicit awareness of the repeating sequence. In addition, past work [27, 48] has not shown a benefit of explicit knowledge for motor learning of tracking tasks. Based on the results of our explicit tests we are confident that our data reflect changes associated with the implicit motor learning system.
We were surprised at the large number (n = 16) of individuals who required TMS intensity to be reduced owing to inadvertent motor twitching during PMd stimulation. These individuals were from the Excite and Inhibit groups alike. One possible explanation is that the threshold for stimulating primary motor cortex (from which we derived our resting motor threshold) is not the same as the threshold in other brain regions [45, 49]. Specifically, it is possible that PMd has a lower threshold for stimulation than M1; thus, stimulation of PMd may have either activated M1 via PMd-M1 connections or recruited descending tracts from PMd that normally would not fire at lower intensities. Future work will have to endeavor to develop methods for thresholding stimulation intensity more appropriately for regions outside motor cortex.
Taken together, our data support a role for PMd in motor memory consolidation through the process of off-line learning. In addition, our findings support the concept that motor memory consolidation may take two distinct forms (off-line improvement and memory stabilization) and that these processes may be dissociated during learning of the same task [6, 7]. Though it is likely that 5 HZ rTMS increased activation in a network of brain regions, we did note a strong influence on excitatory stimulation on memory consolidation suggesting a role for PMd in motor learning. Importantly, the positive effect of 5 HZ rTMS to PMd was directly related to sequence-specific motor learning and had little effect on generalized motor control during continuous tracking.
b0 = 2.0, a1 = -4.0, b1 = 3.0, a2 = -4.9, b2 = -3.6, a3 = 3.9, b3 = 4.5, a4 = 0.0, b4 = 1.0, a5 = -3.8, b5 = -0.5, a6 = 1.0, and b6 = 2.5
Support from the North Growth Foundation and Michael Smith Foundation for Health Research awards (LAB) funded this work. The authors thank Sean Meehan, PhD and Brenda Wessel, MS for their comments on this manuscript.
- Karni A, Meyer G, Rey-Hipolito C, Jezzard P, Adams MM, Turner R, Ungerleider LG: The acquisition of skilled motor performance: Fast and slow experience-driven changes in primary motor cortex. Proceedings of the National Academy of Science (USA). 1998, 95: 861-868. 10.1073/pnas.95.3.861.View ArticleGoogle Scholar
- Boyd LA, Vidoni ED, Siengsukon CF: Multidimensional motor sequence learning is impaired in older but not younger or middle-aged adults. Phys Ther. 2008, 88 (3): 351-362.View ArticlePubMedGoogle Scholar
- van Raalten TR, Ramsey NF, Duyn J, Jansma JM: Practice induces function-specific changes in brain activity. PLoS ONE. 2008, 3 (10): e3270-10.1371/journal.pone.0003270.PubMed CentralView ArticlePubMedGoogle Scholar
- Brashers-Krug T, Shadmehr R, Bizzi E: Consolidation in human motor memory. Nature. 1996, 382: 252-255. 10.1038/382252a0.View ArticlePubMedGoogle Scholar
- Shadmehr R, Holcomb HH: Neural correlates of motor memory consolidation. Science. 1997, 277 (5327): 821-825. 10.1126/science.277.5327.821.View ArticlePubMedGoogle Scholar
- Robertson EM, Cohen DA: Understanding consolidation through the architecture of memories. Neuroscientist. 2006, 12 (3): 261-271. 10.1177/1073858406287935.View ArticlePubMedGoogle Scholar
- Robertson EM, Pascual-Leone A, Miall RC: Current concepts in procedural consolidation. Nature reviews. 2004, 5 (7): 576-582. 10.1038/nrn1426.View ArticlePubMedGoogle Scholar
- Goedert KM, Willingham DB: Patterns of interference in sequence learning and prism adaptation inconsistent with the consolidation hypothesis. Learn Mem. 2002, 9 (5): 279-292. 10.1101/lm.50102.PubMed CentralView ArticlePubMedGoogle Scholar
- Korman M, Raz N, Flash T, Karni A: Multiple shifts in the representation of a motor sequence during the acquisition of skilled performance. Proceedings of the National Academy of Sciences of the United States of America. 2003, 100 (21): 12492-12497. 10.1073/pnas.2035019100.PubMed CentralView ArticlePubMedGoogle Scholar
- Pascual-Leone A, Grafman J, Hallett M: Modulation of cortical motor output maps during development of implicit and explicit knowledge. Science. 1994, 263 (5151): 1287-1289. 10.1126/science.8122113.View ArticlePubMedGoogle Scholar
- Walker MP, Stickgold R, Jolesz FA, Yoo SS: The functional anatomy of sleep-dependent visual skill learning. Cereb Cortex. 2005, 15 (11): 1666-1675. 10.1093/cercor/bhi043.View ArticlePubMedGoogle Scholar
- Rushworth MF, Johansen-Berg H, Gobel SM, Devlin JT: The left parietal and premotor cortices: motor attention and selection. NeuroImage. 2003, 20 (Suppl 1): S89-100. 10.1016/j.neuroimage.2003.09.011.View ArticlePubMedGoogle Scholar
- Kalaska JF, Crammond DJ: Deciding not to GO: neuronal correlates of response selection in a GO/NOGO task in primate premotor and parietal cortex. Cereb Cortex. 1995, 5 (5): 410-428. 10.1093/cercor/5.5.410.View ArticlePubMedGoogle Scholar
- Dum RP, Strick PL, Humphrey DR, Freund HJ: Premotor areas: Nodal points for parallel efferent systems involved in the central control of movement. Motor Control: Concepts and Issues. 1991, John Wiley & Sons Ltd, 383-397.Google Scholar
- Picard N, Strick PL: Motor areas of the medial wall: A review of their location and functional activation. Cerebral Cortex. 1996, 6: 342-353. 10.1093/cercor/6.3.342.View ArticlePubMedGoogle Scholar
- Koch I, Allport A: Cue-based preparation and stimulus-based priming of tasks in task switching. Memory & cognition. 2006, 34 (2): 433-444.View ArticleGoogle Scholar
- Crammond DJ, Kalaska JF: Differential relation of discharge in primary motor cortex and premotor cortex to movements versus actively maintained postures during a reaching task. Exp Brain Res. 1996, 108 (1): 45-61. 10.1007/BF00242903.View ArticlePubMedGoogle Scholar
- Thoenissen D, Zilles K, Toni I: Differential involvement of parietal and precentral regions in movement preparation and motor intention. J Neurosci. 2002, 22 (20): 9024-9034.PubMedGoogle Scholar
- Schluter ND, Krams M, Rushworth MF, Passingham RE: Cerebral dominance for action in the human brain: the selection of actions. Neuropsychologia. 2001, 39 (2): 105-113. 10.1016/S0028-3932(00)00105-6.View ArticlePubMedGoogle Scholar
- Chen YC, Thaler D, Nixon PD, Stern C, Passingham RE: The functions of the medial premotor cortex (SMA) II. The timing and selection of learned movements. Experimental Brain Research. 1995, 102: 461-473. 10.1007/BF00230650.View ArticlePubMedGoogle Scholar
- Johansen-Berg H, Rushworth MFS, Bogdanovic MD, Kischka U, Wimalaratna S, Matthews PM: The role of ipsilateral premotor cortex in hand movement after stroke. Proceedings of the National Academy of Sciences of the United States of America. 2002, 99 (22): 14518-14523. 10.1073/pnas.222536799.PubMed CentralView ArticlePubMedGoogle Scholar
- Ohbayashi M, Ohki K, Miyashita Y: Conversion of working memory to motor sequence in the monkey premotor cortex. Science. 2003, 301 (5630): 233-236. 10.1126/science.1084884.View ArticlePubMedGoogle Scholar
- Salmoni AW, Schmidt RA, Walter CB: Knowledge of results and motor learning: a review and critical reappraisal. Psychol Bull. 1984, 95 (3): 355-386. 10.1037/0033-2909.95.3.355.View ArticlePubMedGoogle Scholar
- Schmidt RA, Lee TD: Motor Control and Learning: A Behavioral Emphasis. 2005, Champaign: Human KineticsGoogle Scholar
- Lundy-Ekman L: Neuroscience: Fundamentals for Rehabilitation. 1998, Philadelphia: WB SaundersGoogle Scholar
- Wulf G, Schmidt RA: Variability of practice and implicit motor learning. Journal of Experimental Psychology: Learning, Memory and Cognition. 1997, 23 (4): 987-1006. 10.1037/0278-7318.104.22.1687.Google Scholar
- Boyd LA, Winstein CJ: Providing explicit information disrupts implicit motor learning after basal ganglia stroke. Learning & Memory. 2004, 11 (4): 388-396. 10.1101/lm.80104.View ArticleGoogle Scholar
- Boyd LA, Winstein CJ: Cerebellar stroke impairs temporal but not spatial accuracy during implicit motor learning. Neurorehabilitation and neural repair. 2004, 18: 134-143. 10.1177/0888439004269072.View ArticlePubMedGoogle Scholar
- Vidoni ED, Boyd LA: Motor sequence learning occurs despite disrupted visual and proprioceptive feedback. Behav Brain Funct. 2008, 4: 32-10.1186/1744-9081-4-32.PubMed CentralView ArticlePubMedGoogle Scholar
- Yousry TA, Schmid UD, Alkadhi H, Schmidt D, Peraud A, Buettner A, Winkler P: Localization of the motor hand area to a knob on the precentral gyrus. A new landmark. Brain. 1997, 120 (Pt 1): 141-157. 10.1093/brain/120.1.141.View ArticlePubMedGoogle Scholar
- Wassermann EM, Wang B, Zeffiro TA, Sadato N, Pascual-Leone A, Toro C, Hallett M: Locating the motor cortex on the MRI with transcranial magnetic stimulation and PET. NeuroImage. 1996, 3 (1): 1-9. 10.1006/nimg.1996.0001.View ArticlePubMedGoogle Scholar
- Boroojerdi B, Foltys H, Krings T, Spetzger U, Thron A, Topper R: Localization of the motor hand area using transcranial magnetic stimulation and functional magnetic resonance imaging. Clin Neurophysiol. 1999, 110 (4): 699-704. 10.1016/S1388-2457(98)00027-3.View ArticlePubMedGoogle Scholar
- Dassonville P, Lewis SM, Zhu XH, Ugurbil K, Kim SG, Ashe J: The effect of stimulus-response compatibility on cortical motor activation. NeuroImage. 2001, 13 (1): 1-14. 10.1006/nimg.2000.0671.View ArticlePubMedGoogle Scholar
- Dassonville P, Lewis SM, Zhu XH, Ugurbil K, Kim SG, Ashe J: Effects of movement predictability on cortical motor activation. Neurosci Res. 1998, 32 (1): 65-74. 10.1016/S0168-0102(98)00064-9.View ArticlePubMedGoogle Scholar
- Fridman EA, Hanakawa T, Chung M, Hummel F, Leiguarda RC, Cohen LG: Reorganization of the human ipsilesional premotor cortex after stroke. Brain. 2004, 127 (Pt 4): 747-758. 10.1093/brain/awh082.View ArticlePubMedGoogle Scholar
- Toni I, Passingham RE: Prefrontal-basal ganglia pathways are involved in the learning of arbitrary visuomotor associations: a PET study. Exp Brain Res. 1999, 127 (1): 19-32. 10.1007/s002210050770.View ArticlePubMedGoogle Scholar
- Gerschlager W, Siebner HR, Rothwell JC: Decreased corticospinal excitability after subthreshold 1 Hz rTMS over lateral premotor cortex. Neurology. 2001, 57 (3): 449-455.View ArticlePubMedGoogle Scholar
- Munchau A, Bloem BR, Irlbacher K, Trimble MR, Rothwell JC: Functional connectivity of human premotor and motor cortex explored with repetitive transcranial magnetic stimulation. J Neurosci. 2002, 22 (2): 554-561.PubMedGoogle Scholar
- Ruohonen J, Ilmoniemi RJ: Physical principles for transcranial magnetic stimulation. Handbook of Transcranial Magnetic Stimulation. Edited by: Pascual-Leone A, Davey NJ, Rothwell J, Wassermann EM, Puri BK. 2002, New York: Arnold, 24-FirstGoogle Scholar
- Chouinard PA, Leonard G, Paus T: Role of the primary motor and dorsal premotor cortices in the anticipation of forces during object lifting. J Neurosci. 2005, 25 (9): 2277-2284. 10.1523/JNEUROSCI.4649-04.2005.View ArticlePubMedGoogle Scholar
- Foltys H, Krings T, Meister IG, Sparing R, Boroojerdi B, Thron A, Topper R: Motor representation in patients rapidly recovering after stroke: a functional magnetic resonance imaging and transcranial magnetic stimulation study. Clin Neurophysiol. 2003, 114 (12): 2404-2415. 10.1016/S1388-2457(03)00263-3.View ArticlePubMedGoogle Scholar
- Chen WH, Mima T, Siebner HR, Oga T, Hara H, Satow T, Begum T, Nagamine T, Shibasaki H: Low-frequency rTMS over lateral premotor cortex induces lasting changes in regional activation and functional coupling of cortical motor areas. Clin Neurophysiol. 2003, 114 (9): 1628-1637. 10.1016/S1388-2457(03)00063-4.View ArticlePubMedGoogle Scholar
- Boyd LA, Quaney BM, Pohl PS, Winstein CJ: Learning implicitly: effects of task and severity after stroke. Neurorehabilitation and neural repair. 2007, 21 (5): 444-454. 10.1177/1545968307300438.View ArticlePubMedGoogle Scholar
- Robertson EM: Skill learning: putting procedural consolidation in context. Curr Biol. 2004, 14 (24): R1061-1063. 10.1016/j.cub.2004.11.048.View ArticlePubMedGoogle Scholar
- Bestmann S, Baudewig J, Siebner HR, Rothwell JC, Frahm J: BOLD MRI responses to repetitive TMS over human dorsal premotor cortex. NeuroImage. 2005, 28 (1): 22-29. 10.1016/j.neuroimage.2005.05.027.View ArticlePubMedGoogle Scholar
- Shea CH, Wulf G, Whitacre CA, Park JH: Surfing the implicit wave. Q J Exp Psychol A. 2001, 54 (3): 841-862. 10.1080/02724980042000381.View ArticlePubMedGoogle Scholar
- Robertson EM, Press DZ, Pascual-Leone A: Off-line learning and the primary motor cortex. J Neurosci. 2005, 25 (27): 6372-6378. 10.1523/JNEUROSCI.1851-05.2005.View ArticlePubMedGoogle Scholar
- Green TD, Flowers JH: Implicit versus explicit learning processes in a probabilistic, continuous fine-motor catching task. Journal of motor behavior. 1991, 23: 293-300.View ArticlePubMedGoogle Scholar
- Stewart LM, Walsh V, Rothwell JC: Motor and phosphene thresholds: a transcranial magnetic stimulation correlation study. Neuropsychologia. 2001, 39 (4): 415-419. 10.1016/S0028-3932(00)00130-5.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.